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2018 | OriginalPaper | Chapter

A Brain-Inspired Cognitive System that Mimics the Dynamics of Human Thought

Authors : Yuehu Ji, David Gamez, Christian Huyck

Published in: Artificial Intelligence XXXV

Publisher: Springer International Publishing

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Abstract

In recent years, some impressive AI systems have been built that can play games and answer questions about large quantities of data. However, we are still a very long way from AI systems that can think and learn in a human-like way. We have a great deal of information about how the brain works and can simulate networks of hundreds of millions of neurons. So it seems likely that we could use our neuroscientific knowledge to build brain-inspired artificial intelligence that acts like humans on similar timescales. This paper describes an AI system that we have built using a brain-inspired network of artificial spiking neurons. On a word recognition and colour naming task our system behaves like human subjects on a similar timescale. In the longer term, this type of AI technology could lead to more flexible general purpose artificial intelligence and to more natural human-computer interaction.

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previous chapter Informed Pair Selection for Self-paced Metric Learning in Siamese Neural Networks

next chapter Enhancing Human Decision Making for Workforce Optimisation Using a Stacked Auto Encoder Based Hybrid Genetic Algorithm

The code can be found on http://www.cwa.mdx.ac.uk/NEAL/NEAL.html.

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Title: A Brain-Inspired Cognitive System that Mimics the Dynamics of Human Thought
Authors: Yuehu Ji
David Gamez
Christian Huyck
Publisher: Springer International Publishing
Book: Artificial Intelligence XXXV
Print ISBN: 978-3-030-04190-8

Electronic ISBN: 978-3-030-04191-5

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-04191-5_4

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